code: def testTensorFlowToJax(self, shape, dtype):
      if xb.using_pjrt_c_api():
          self.skipTest(
              "DLPack support is incomplete in the PJRT C API"
          )
      if not config.enable_x64.value and dtype in [
          jnp.int64,
          jnp.uint64,
          jnp.float64,
      ]:
          raise self.skipTest(
              "x64 types are disabled by jax_enable_x64"
          )
      if jtu.test_device_matches(
          ["gpu"]
      ) and not tf.config.list_physical_devices("GPU"):
          raise self.skipTest(
              "TensorFlow not configured with GPU support"
          )
  
      if jtu.test_device_matches(["gpu"]) and dtype == jnp.int32:
          raise self.skipTest(
              "TensorFlow does not place int32 tensors on GPU"
          )
  
      rng = jtu.rand_default(self.rng())
      np = rng(shape, dtype)
      with tf.device(
          "/GPU:0" if jtu.test_device_matches(["gpu"]) else "/CPU:0"
      ):
          x = tf.identity(tf.constant(np))
      dlpack = tf.experimental.dlpack.to_dlpack(x)
      y = jax.dlpack.from_dlpack(dlpack)
      self.assertAllClose(np, y)
  
imports: import unittest
  from absl.testing import absltest
  import jax
  import jax.dlpack
  import jax.numpy
  from jax._src import config
  from jax._src import test_util
  from jax._src import xla_bridge
  from jax._src.lib import xla_extension_version
  import numpy
label_desc: Use image node_id 4 for calling the DLPackTest obj's underlying member method code with example usage: obj.testTensorFlowToJax(shape, dtype) without return types